The aging population is the largest consumer base of prescribed medications, with 40% of older adults managing 5 or more drugs. However, approximately 50% of these prescribed medications are not taken as directed. Repercussions from nonadherence in the aging population include an annual $100 to $289 billion dollars in health care costs, inaccurate efficacy results for clinical drug trials and significant public health issues like increased rates of comorbid diseases and anti-biotic resistance. The long-term objective of this project is to build a quick, reliable and ecological valid clinical assessment to capture cognitive-related nonadherence risk and to develop tailored interventions to reduce nonadherence. The primary objective of this application is to test four medication adherence components hypothesized to be contributors of cognitive-related medication nonadherence in older adults and, therefore, necessary for inclusion in such a clinical assessment of functioning (i.e., performance-based measure). Building on my prior work, the approach will be to examine relationships between real-world adherence and performance-based measures of medication knowledge, management, prospective memory and compensatory strategy problem-solving abilities (Aims 1-3). In addition, the proposed research will demonstrate how each performance-based measure independently captures aspects of real-world medication adherence above and beyond known neuropsychological correlates (Aim 1-3). Finally, performance-based measures that best predict real-world medication adherence will be identified by using hierarchical regressions to analyze the relationships between the performance-based measures and real-world medication adherence (Aim 4). A quick ecologically valid assessment for cognitive- related nonadherence is expected to provide the research and clinical community a tool to identify medication nonadherence risk. The approach is innovative because it will (a) monitor and measure medication adherence using the participant?s everyday medication devices (i.e., using Estimotes, thin attachable movement sensors); (b) examine the relationship between medication performance-based measures and real-world adherence; and (c) utilize novel medication performance-based measures to examine abilities thought to be critical to supporting real-world adherence (i.e., prospective memory and compensatory strategy problem-solving, unexamined aspects of medication adherence). A measure of medication functional capacity is significant because it extends medication nonadherence measurements beyond self-reports and captures real-world cognitive-related medication nonadherence risk. Therefore, this measure has the potential to aid in diagnostic decision making and identifying specific medication functional deficits that could be targeted with interventions. Given the significant burden of cognitive-related medication nonadherence, this measure is expected to have a downstream impact on reducing national rates of preventable disability and mortality, emergency room visits, comorbid chronic diseases and health care costs.